R Is Still Hot – and Getting Hotter

When I wrote a white paper titled “R Is Hot” about four years ago, my goal was to introduce the R programming language to a larger audience of statistical analysts and data scientists. As it turned out, the timing couldn’t have been bet...

Revolution R Plus

Revolution R Plus is the enhanced and supported distribution of the world's most widely used statistical data analysis software, open source R. A complete platform for data science and building data driven applications, Revolution R Plu...

Free Course: Introduction to Revolution R...

Revolution R Enterprise allows R users to process, visualize, and model terabyte- class data sets at a fraction of the time of legacy products without requiring expensive or specialized hardware. This is an introductory course for accom...

Revolution R Enterprise: Faster Than SAS

In analytics, speed matters. How much? We asked the director of analytics from a leading U.S. marketing services provider, a Revolution Analytics customer. Her team supports more than 1,000 predictive models currently in production; her...

The Revolution Analytics perspective on Big Data

When it comes to Big Data, it’s “one thing to be able to query it, but it’s another thing to be able to actually ask that data meaningful questions,” according to Revolution Analytics head of marketing and community David Smith. The exe...

Finding Meaning in Points, Areas and Surfaces: Spatial Analysis in R

Presenters:

In this webinar, David will present three real-world examples of how spatial statistics are used, each illustrating the analysis of a particular class of spatial data (points, areas and surfaces) with a particular R package (spatstat, maptools, sp, spdep, gstat). He will show the flexibility and power that are gained when the R route is chosen. Join us to explore these uses of spatial data:

In geology, we attempt to answer the question ‘are the glacial hills called drumlins randomly distributed?

In epidemiology we ask the question ‘where is there an unusual incidence of a disease?

And in environmental science we ask ‘what is the value of this spatially continuous variable at this location?

David will also touch on other possibilities: there are packages for lines and network data, for image data, and for easy ‘mash ups onto Google ™ Maps and Earth.